Closely coupled object detection and segmentation

TitleClosely coupled object detection and segmentation
Publication TypeConference Papers
Year of Publication2005
AuthorsZhao L, Davis LS
Conference NameComputer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on
Date Published2005///

We propose a closely coupled object detection and segmentation algorithm for enhancing both processes in a cooperative and iterative manner. Figure-ground segmentation reduces the effect of background clutter on template matching; the matched template provides shape constraints on segmentation. More precisely, we estimate the probability of each pixel belonging to the foreground by a weighted sum of the estimates based on shape and color alone. The weight on the shape-based estimate is related to the probability that a familiar object is present and is updated dynamically so that we enforce shape constraints only where the object is present. Experiments on detecting people in images of cluttered scenes demonstrate that the proposed algorithm improves both segmentation and detection. More accurate object boundaries are extracted; higher object detection rates and lower false alarm rates are achieved than performing the two processes separately or sequentially.